For radio communications systems, in which data is transmitted over the air interface from a transmitting unit to a receiving unit, it is known from the state of the art to transmit the respective data either in uncoded or in coded form.
Coding of to be transmitted data is used in order to be able to detect and/or correct the errors occurring in the transmission of data on the transmission path on the air interface. In systematic coding methods, e.g., for all data, systematic and parity bits are created. The systematic bits correspond to the data in uncoded form and the parity bits constitute additional, coded redundant information. For a coding rate of ⅓, for example, a systematic encoder provides for each systematic bit two parity bits.
Turbo coding is a systematic coding method that uses recursive, systematic convolutional codes. The parity bits are provided by different constituent encoders using different constituent polynomials. The decoding is carried out iteratively in order to obtain a good error correction performance.
Parallel concatenated turbo codes differ in the way the constituent polynomials are defined and in the way interleaving is done. The polynomials are searched for a given operating point, bearing in mind complexity requirements. As in the other known coding methods, all encoded bits are transmitted with equal power. In case the actual operating point differs from the operating point for which the polynomials were determined, e.g. because of changed channel conditions, the fixed polynomials do not result any more in the best performance of coding.
It is known to vary an employed code by a method called puncturing, according to which every nth bit of a code is left out, thus reducing the coding rate, but this allows only for a limited adaptation to channel conditions.
FIGS. 1 and 2, which were extracted from “Turbo Coding” by Chris Heegard and Stephen B. Wicker, Kluwer Academic Publishers, oppose for two different turbo decoding methods the performance obtained with transmitted coded data and the performance obtained with transmitted uncoded data.
In both figures, the BER (bit error rate) is depicted over the Eb/No (Eb=energy per bit; No=noise power density per Hz). Four curves with asterisk illustrate in each figure the performance with coded data based on different numbers of iterations in decoding. The number next to each curve indicates the number of iterations carried out. A further curve-without asterisk illustrates in each figure the performance with uncoded data.
FIG. 1 is based on serial turbo decoding. It can be seen that the BER of the uncoded data is better than the BER of coded data irrespective of the number of iterations for a Eb/No below approximately 1.1 dB. For higher Eb/No, in contrast, the BER of the coded data is better than the BER of the uncoded data, the respective threshold value of the Eb/No depending on the number of iterations used for decoding.
FIG. 2 is based on parallel turbo decoding. As can be seen in the diagram, the threshold value of the Eb/No for which the performance with uncoded data is better than with coded data depending on the number of iterations is reduced, but in particular for lower numbers of iterations, there still exist a range of better channel conditions, in which uncoded data results in a better performance.
FIGS. 1 and 2 therefore illustrate that the conventional turbo coding methods are not suited to enable an optimal coding performance for all channel conditions.